class: center, middle, inverse, title-slide .title[ # Unveiling the Impacts of Brazil’s Unique Fuel Mix on Air Quality: A Century of Vehicular Emissions ] .author[ ### Sergio Ibarra-Espinosa¹ ² ] .author[ ### CIRES, University of Colorado-Boulder ] .date[ ### 2025-03-21 ] --- class: inverse center middle ## Unveiling the Impacts of Brazil's Unique Fuel Mix on Air Quality: A Century of Vehicular Emissions > Sergio Ibarra-Espinosa¹'² <br> > CIRES, University of Colorado-Boulder<br> > sergio.ibarraespinosa@colorado.edu<br> > Collaboratory for Air Quality Research (CAQR) Department Mechanical Engineering University of Colorado-Boulder <img src="https://atmoschem.github.io/vein/reference/figures/logo.png" alt="drawing" height="100"/> <img src="https://github.com/atmoschem/respeciate/blob/main/man/figures/logo.png?raw=true" alt="drawing" height="100"/> <img src="https://atmoschem.github.io/eixport/reference/figures/logo.gif" alt="drawing" height="100"/> <img src="https://www2.acom.ucar.edu/sites/default/files/styles/extra_large/public/images/MUSICAlogo_0.png" alt="drawing" height="100"/> <img src="https://avatars.githubusercontent.com/u/12666893?s=200&v=4" alt="drawing" height="100"/> - extra slides: VEIN+MOVES in US, China, WRF Chem, Methane Emissions over US --- class: centered inverse middle > “Emission inventories are easily seen as the scapegoat if a mismatch is found between modelled and observed concentrations of air pollutants”. Pulles, Tim, and Dick Heslinga. "The art of emission inventorying." TNO, Utrecht (2010): 29-53. --- # Emissions inventories .pull-left[ ## Global inventories - Crippa et al., (2024) Emissions Database for Global Atmospheric Research (EDGAR) 1970-2023 - Feng at al., (2020) Community Emissions Data System (CEDS) - Soulie et al., (2024) CAMS inventory 2000-2025 ] .pull-right[ ## Regional inventories - Osses et al (2022): Chile 1990-2020 - Rojas et al., (2023): Colombia 1990-2020 - MMA-Brazil, (2011): Brazil 1989-2020 - Hoinaski et al., (2022): Brazil 2013-2019 - Puliafito et al., (2021): Argentina 1995-2020 ] --- # History of road transportation in Brazil .pull-left[ ## Roads and cars - Brazil has the biggest fleet in Latin America, with big problems in air pollution and congestion. - In 1930s, President Getúlio Vargas initiated first large road projects, including the construction of the "Via Dutra" (Dutra Highway), which connected Rio de Janeiro to São Paulo. - In 1950, President Kubitschek' Large-scale road construction began, aiming to attract the automotive industry. - Volkswagen, Ford and General Motors arrived in Brasil . - Today, fleet more than 200 million. ] .pull-right[ ## Cars <img src="https://upload.wikimedia.org/wikipedia/commons/9/90/Romi-Isetta_%C3%81guas_de_Lind%C3%B3ia.jpg" alt="First car made in Brasil" height="200"/> - First car produced in Brazil in 1955 - https://en.wikipedia.org/wiki/Isetta#Romi-Isetta_(Brazil) ] --- # Fuel, fleet and technology .pull-left[ ## Fuel - Gasoline contains 27% of ethanol. - Diesel has 7% biodiesel - In 2003, flex engine emerged, allowing any mix of gasoline or ethanol - Ethanol is cheaper, but a bit less miles per gallon - In 2009, flex engines where incorporated into motorcycles - Today, 76% of the fleet are flex vehicles ] .pull-right[ ## Fleet - Light vehicles (PC, LCV, MC) with gasoline engine, with ethanol engine, and flex - LCV vehicles also consume diesel - Trucks consume diesel - Buses consume mostly diesel - Small participation: electric cars - **Electric vehicles are less environmentally friendly than flex-fuel cars considering a broader analysis (de Oliveira et al., 2020)**. - https://www.epa.gov/greenvehicles/electric-vehicle-myths ] --- # Objectives - Estimate vehicular emission in Brazil, 1960-2100 - Evaluate impact of Shared Socioeconomic Pathways on evaporative emissions - Evaluate impacts on air quality during 2019 - Compare with Lichtig et al. (2024) --- class: inverse center middle # Data and methods --- # Fuel .pull-left[ - Fleet State of Sao Paulo 1979-2020 (CETESB, 2023) - Mileage from Official vehicular inventory (CETESB, 2023) - Monthly fuel consumption by state, 2000-2023 (ANP, 2023) $$ f(x)=\frac{L}{e^{-k(x - x_0)}} $$ ] .pull-right[ <img src="figuras/fuela.jpg" alt="fuel" height="500"/> ] --- # Fleet and fuel in 2020 .pull-left[ <img src="figuras/initial_fleet_sp.png" alt="fleet sp" height="500"/> ] .pull-right[ <img src="figuras/fuelb.jpg" alt="fuelb" height="500"/> ] --- # Vehicular Emissions INventories vein .pull-left[ * build: [](https://ci.appveyor.com/project/ibarraespinosa/vein) [](https://codecov.io/github/atmoschem/vein?branch=master) * cran: [](http://cran.rstudio.com/web/packages/vein/index.html) [](http://cran.r-project.org/web/packages/vein) [](http://cran.r-project.org/package=vein) [](https://www.tidyverse.org/lifecycle/#maturing)  * doi: [](https://zenodo.org/badge/latestdoi/88201850) * github: [](https://github.com/atmoschem/vein)   <!--  -->  [](https://github.com/atmoschem/vein/actions) - R package to calculate vehicular emissions - Includes Fortran subroutines with // OpenMP - main paper: https://gmd.copernicus.org/articles/11/2209/2018/ - 64 citations [(2018)](https://scholar.google.com/scholar?oi=bibs&hl=en&cites=1650173053278606175) - Detailed speciation applying Carter [(2015)](https://www.tandfonline.com/doi/full/10.1080/10962247.2015.1013646) - YouTube Channel https://www.youtube.com/channel/UC2oYaS9mpnIDk8w55O8_bTg - Emission factors based on real world measurements ] .pull-right[ <img src="https://atmoschem.github.io/vein/reference/figures/logo.png" height="100"/> <image src="https://atmoschem.github.io/eixport/reference/figures/logo.gif" height="100"> <image src="https://github.com/atmoschem/respeciate/blob/main/man/figures/logo.png?raw=true" height="100"> <img src="https://user-images.githubusercontent.com/520851/34887433-ce1d130e-f7c6-11e7-83fc-d60ad4fae6bd.gif" height="100"/> <img src="https://raw.githubusercontent.com/Rdatatable/data.table/master/.graphics/logo.png" height="100"/> ] --- # vein  --- # How to run vein (without knowing R) .pull-left[ - Install and get a [project](https://atmoschem.github.io/vein/reference/get_project.html) ``` r install.packages("vein") library(vein) ?get_project ``` ] .pull-right[ <image src="figuras/vein_projects.jpg" height="500"> ] --- # MUSICA (ACOM NSF NCAR) .pull-left[ - [MUSICA](https://wiki.ucar.edu/display/MUSICA/MUSICA+Home) - The Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) will become a computationally feasible global modeling framework that allows for the simulation of large-scale atmospheric phenomena, while still resolving chemistry at emission and exposure relevant scales. - MUSICAv0 is a configuration of CAM-chem, the Community Atmosphere Model with chemistry, component of the Community Earth System Model (CESM). - Configuration: Spectral Element (SE) dynamical core, which allows for Regional Refinement (RR), so is called CAM-chem-SE-RR, or MUSICAv0. - The chemical mechanism in MUSICA is MOZART-TS1 (Emmons et al., 2020) - Aerosols Modal Aerosol Module (MAM4) with volatility bin set (VBS) (Liu et al., 2016; Tilmes et al., 2019). ] .pull-right[ <image src="figuras/grids/grids.gif" height="400"> ] --- # Grid South America <img src="figuras/o3mus5.png" width="93%" style="display: block; margin: auto;" /> --- # VEIN + MUSICA .pull-left[ ## Emissions - Fire INventory from NCAR version 2.5 (FINNv2.5) (Wiedinmyer,et al., 2023) - CAMS (Soulie et al., 2023) - Biogenic emissions the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (Guenther et al., 2012). - Transportation Emisisons from VEIN In Brazil ] .pull-right[ ## Scenarios 1. MUSICA 2018 and 2019 with default emissions 2. MUSICA 2018 and 2019 with transportation from VEIN in Brazil and other elsewhere ] --- class: inverse center middle # Results --- class: center middle <img src="figuras/vein_ceds_edgar_cams_CO2.png" alt="drawing" height="550"/> --- class: center middle <img src="figuras/vein_ceds_edgar_cams.png" alt="drawing" height="550"/> --- class: center middle <img src="figuras/vein_ceds_edgar_cams_PM.png" alt="drawing" height="550"/> --- class: center middle <img src="figuras/vein_ceds_edgar_cams_NMHC.png" alt="drawing" /> --- class: inverse center middle # Is there a positive feedback with evaporative emissions? --- # hockey-type curve - Based on last figures, it seems that there is indeed a positive feedback - The hotter the air, the more evaporative emissions, hence more global warming - To investigate the breakpoints, we used Regression Model with Segmented Relationship(s) - We used the R package segmented - Fasola S, Muggeo VMR, Kuchenhoff K. (2018). A heuristic, iterative algorithm for change-point detection in abrupt change models. Computational Statistics, 33, 997-1015. --- class: center middle <img src="figuras/vein_ceds_edgar_cams_hockey_brazil.png" alt="drawing" /> --- class: center middle <img src="figuras/vein_ceds_edgar_cams_hockey_region.png" alt="drawing" /> --- class: inverse center middle # Maps VEIN CAMS --- class: center middle #CO .pull-left[ <img src="figuras/vein_cams_co.png" alt="drawing" /> ] .pull-right[ <img src="figuras/vein_cams_co_dif.png" alt="drawing" height="500"/> ] --- class: center middle #NOx .pull-left[ <img src="figuras/vein_cams_nox.png" alt="drawing" /> ] .pull-right[ <img src="figuras/vein_cams_nox_dif.png" alt="drawing" height="500"/> ] --- class: center middle #alcohols .pull-left[ <img src="figuras/vein_cams_alcohols.png" alt="drawing" /> ] .pull-right[ <img src="figuras/vein_cams_alcohols_dif.png" alt="drawing" height="500"/> ] --- class: center middle #acetylene .pull-left[ <img src="figuras/vein_cams_acetylene.png" alt="drawing" /> ] .pull-right[ <img src="figuras/vein_cams_acetylene_dif.png" alt="drawing" height="500"/> ] --- class: inverse center middle # Some advances using MUSICA --- ## MUSICA run over South America <img src="figuras/o3mus5.png" width="93%" style="display: block; margin: auto;" /> --- class: inverse center middle # Gracias! .pull-left[ - https://ibarraespinosa.github.io/2025CU - https://ibarraespinosa.github.io/ - sergio.ibarraespinosa@colorado.edu - https://scholar.google.com.br/citations?user=8ohZGHEAAAAJ - https://github.com/ibarraespinosa - https://www.researchgate.net/profile/Sergio_Ibarra-Espinosa - https://orcid.org/0000-0002-3162-1905 ] .pull-right[ <img src="figuras/qr.png" alt="drawing" height="400"/> ] --- class: center ## WRF Chemi using eixport <video width="520" height="440" controls> <source src="wrfc.mp4" type="video/mp4" height="550"/> Your browser does not support the video tag. </video> --- class: inverse center middle # Integration with US/EPA MOVES --- ## Recent Research: Integration of MOVES and VEIN: - MOVES is the official vehicular emissions model for US. Runs on Windows, written in Java/SQL with MariaDB. VEIN is very versatile, ideal for traffic flow at streets. Currently has two approaches: - **1** Estimation using Windows with MOVES >3.0 installed. Emission factors are accessed using SQL in R. - **2** Estimation using any OS. Emission factors are exported from Windows as .csv.gz and read with `data.table::fread`. - Paper will be submitted to GMD (under development) --- ## Screenshots ``` r vein::get_project(directory = "sacramento", case = "moves") ``` .pull-left[ <img src="figuras/main.png" width="83%" style="display: block; margin: auto;" /> ] .pull-right[ <img src="figuras/moves1.png" width="75%" style="display: block; margin: auto;" /> ] --- ## Sacramento County 2017 .left-column[ - Traffic flow for a 4-stage travel demand model output for Sacramento Area, extracted for Sacramento County.' - Traffic flow is for 2016 from CARB. - Traffic flow is total traffic volume 08:00-09:00. - Vehicular composition based on baltimore. - Fuel consumption for 2017. - Emission factors from Baltimore 2017. - Temporal factors from hourly VMT MOVES Baltimore. - Assumed BPR parameters. ] .right-column[
] --- class: center ## Speed parameters .pull-left[ <img src="figuras/SPEED.png" alt="drawing" height="500"/> ] .pull-right[ <img src="figuras/SPEEDBIN.png" alt="drawing" height="500"/> ] --- ## Emissions .pull-left[ <img src="figuras/emisac.png" width="93%" style="display: block; margin: auto;" /> ] .pull-right[ <img src="figuras/no2mov.png" width="93%" style="display: block; margin: auto;" /> ] --- ## Spatial Emissions ``` ## Sum of street emissions 10466599.96 ## Sum of gridded emissions 10466599.96 ```